I suppose the part I seem to be missing: what's to stop Facebook from setting up a "Signal Server" that then hosts those users on Whatsapp/Messenger?
From there, what happens if Facebook then attempt to integrate those servers into the existing Signal network?
I'm really not sure how information is shared between servers on Signal and am curious if there's not something at a purely technical level to stop that from happening. I'd imagine there's some keys that need to be passed around for handling en/decryption which I think is what you're alluding to, but I want to be clear that that's what you mean.
Right, but with Signal being an open source project, it seems that anyone could (pending license-ability) build an app to interact with the main Signal network. It's my understanding there's a few apps on F-Droid that let you do that already.
Thus, Facebook should be able to (at least in theory) build compatibility for the Signal network into their existing messengers.
I agree that there's a ton of parallels between now and the period just before WWI (e.g. I've only recently realized how much a tangled web of alliances the Middle East / North East Africa is).
But of all the parallels that could exist, I really think the "men aren't manly enough" attitude we see today / saw them is not a good indicator of us heading towards the next world war. And even if you think it's a good one, I also think there are just way better indicators, to the point that recruiting propaganda trends aren't going to be a major contributor.
Not at all impressive, but to maximize interactions on a newborn thread:
It's probably my PS3, which I would have gotten Christmas 2008 (or maybe it was 2009?). I recently started sailining the seas, and the most convenient way to watch those videos is to burn them to a disk, and so the PS3 is really just a glorified DVD player (can't even be bothered to use it's blue ray functionality)
Liquor Bottle by Herbal T. Has a nice faux-upbeat rhythm with jazzy kinda beats, but lyrics.are dark. Definitely helps me keep a sane face on the dark days:
I don't mean to say that the mechanism by which human brains learn and the mechanism by which AI is trained are 1:1 directly comparable.
I do mean to say that the process looks pretty similar.
My knee jerk reaction is to analogize it as comparing a fish swimming to a bird flying. Sure there are some important distinctions (e.g. bird's need to generate lift while fish can rely on buoyancy) but in general, the two do look pretty similar (i.e. they both take a fluid medium and push it to generate thrust).
And so with that, it feels fair to say that learning, that the storage and retrieval of memories/experiences, and that the way that that stored information shapes our sub-concious (and probably conscious too) reactions to the world around us seems largely comparable to the processes that underlie the training of "AI" and LLMs.
I feel the Turing machine portion is not particularly relevant to the larger point. Not to belabor the point, but to be as clear as I can be: I don't think nor intend to communicate that humans operate in the same way as a computer; I don't mean to say that we have a CPU that handles instructions in a (more or less) one at a time fashion with specific arguments that determine flow of data as a computer would do with Assembly Instructions. I agree that anyone arguing human brains work like that are missing a lot in both neuroscience and computer science.
The part I mean to focus on is the models of how AIs learn, specifically in neutral networks. There might be some merit in likening a cell to a transistor/switch/logic gate for some analogies, but for the purposes of talking about AI, I think comparing a brain cell to a node in a neutral network is most useful.
The individual nodes in neutral network will have minimal impact on converting input to output, yet each one does influence the processing of one to the other. Iand with the way we train AI, how each node tweaks the result will depend solely on the past I put that has been given to it.
In the same way, when met with a situation, our brains will process information in a comparable way: that is, any given input will be processed by a practically uncountable amount of neurons, each influencing our reactions (emotional, physical, chemical, etc) in miniscule ways based on how our past experiences have "treated" those individual neurons.
In that way, I would argue that the processes by which AI are trained and operated are comparable to that of the human mind, though they do seem to lack complexity.
Ninjaedit: I should proofread my post before submitting it.
Yes? I think that depends on your specific definition and requirements of a turing machine, but I think it's fair to compare the almagomation of cells that is me to the "AI" LLM programs of today.
While I do think that the complexity of input, output, and "memory" of LLM AI's is limited in current iterations (and thus makes it feel like a far comparison to "human" intelligence), I do think the underlying process is fundamentally comparable.
The things that make me "intelligent" are just a robust set of memories, lessons, and habits that allow me to assimilate new information and experiences in a way that makes sense to (most of) the people around me. (This is abstracting away that this process is largely governed by chemical reactions, but considering consciousness appears to be just a particularly complicated chemistry problem reinforces the point I'm trying to make, I think).
I don't think that fully encapsulates a counter point, but I think that has the beginnings of a solid counter point to the argument I've laid out above (again, it's not one I actually devised, just one that really put me on my heels).
The ability to recognize when it's out of its depth does not appear to be something modern "AI" can handle.
As I chew on it, I can't help but wonder what it would take to have AI recognize that. It doesn't feel like it should be difficult to have a series of nodes along the information processing matrix to track "confidence levels". Though, I suppose that's kind of what is happening when the creators of these projects try to keep their projects from processing controversial topics. It's my understanding those instances act as something of a short circuit where (if you will) when confidence "that I'm allowed to walk about this" drops below a certain level, the AI will spit out a canned response vs actually attempting to process input against the model.
The above is intended ad more a brain dump than a coherent argument. You've given me something to chew on, and for that I thank you!
The best decision I could make is a guess based on the logic I've determined from my own experiences that I would then compare and contrast to the current input.
I will say that "current input" for humans seems to be more broad than what is achievable for AI and the underlying mechanism that lets us assemble our training set (read as: past experiences) into useful and usable models appears to be more robust than current tech, but to the best of my ability to explain it, this appears to be a comparable operation to what is happening with the current iterations of LLM/AI.
So I understand all that but my counter point: can we prove by empirical measure that humans operate in a way that is significantly different? (If there is, I would love to know because I was cornered by a similar talking point when making a similar argument some weeks ago)
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...so are they going to tell us what the 90+ apps are?